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The human gut microbiota produces diverse, extensive metabolites that have the potential to affect host physiology. Despite significant efforts to identify metabolic pathways for producing these microbial metabolites, a comprehensive metabolic pathway database for the human gut microbiota is still lacking. Here, we present Enteropathway, a metabolic pathway database that integrates 3269 compounds, 3677 reactions, and 876 modules that were obtained from 1012 manually curated scientific literature. Notably, 698 modules of these modules are new entries and cannot be found in any other databases. The database is accessible from a web application (https://enteropathway.org) that offers a metabolic diagram for graphical visualization of metabolic pathways, a customization interface, and an enrichment analysis feature for highlighting enriched modules on the metabolic diagram. Overall, Enteropathway is a comprehensive reference database that can complement widely used databases, and a tool for visual and statistical analysis in human gut microbiota studies and was designed to help researchers pinpoint new insights into the complex interplay between microbiota and host metabolism. [ABSTRACT FROM AUTHOR]

This paper provides an educational tool to help the public better understand the greenhouse gas (GHG) emissions from the food they choose to eat on a daily basis. Using balloons filled with the representative volume of GHGs emitted through the growth, harvest, production, and transportation of various food choices, participants are able to visualize the impact of their food choices without the burden of analyzing a graph or table. Additionally, displaying the typical GHG metric of equivalent kilograms of carbon dioxide (kg CO2e) in the volume this gas would occupy at standard pressure and temperature allows for greater clarity in these results. Distribution methods for this visualization tool described herein range from science classrooms to Science, Technology, Engineering, and Mathematics (STEM) outreach events and to restaurants and grocery stores. Several tools are provided as part of this research, including a spreadsheet that incorporates these calculations, presentation slides, a worksheet for the in-class method, and poster images for eateries. For each method, participants are asked to select a protein, vegetable, and starch option to fill their plate and the resulting GHG volume is then calculated based on their selections. This provides context and allows for discussion and reshaping of our contributions to climate change. [ABSTRACT FROM AUTHOR]

Abstract Massive Open Online Courses (MOOCs) are revolutionizing online education and have become a popular teaching platform. However, traditional MOOCs often overlook learners' individual needs and preferences when designing learning materials and activities, resulting in suboptimal learning experiences. To address this issue, this paper proposes an approach to identify learners' preferences for different learning styles by analyzing their traces in MOOC environments. The Felder–Silverman Learning Style Model is adopted as it is one of the most widely used models in technology-enhanced learning. This research focuses on developing a reliable predictive model that can accurately identify learning styles. Based on insights gained from our model implementation, we propose MOOCLS (MOOC Learning Styles), an intuitive visualization tool. MOOCLS can help teachers and instructional designers to gain significant insight into the diversity of learning styles within their MOOCs. This will allow them to design activities and content that better support the learning styles of their learners, which can lead to higher learning engagement, improved performance, and reduction in time to learn.

Personalized learning is the shaping of instruction to meet students' needs to support student learning and improve learning outcomes. While it has received increasing attention in education, limited resources are available to help educators properly leverage assessment data to foster personalized learning. Motivated by this need, we introduce a new visualization tool, the interaction map, to foster personalized learning based on assessment data. The interaction map approach is engineered by the latent space item response model, a recent development in assessment data-leveraging social network analysis methodologies. In the interaction map, students and test items are mapped into a two-dimensional geometric space, in which their distances tell us about the student's strengths and weaknesses with individual or groups of test items given their overall ability levels. Student profiles can be generated based on these distances to display individual student strengths and weaknesses. Finally, we introduce a user-friendly, free web-based software IntMap in which users can upload their own assessment data and view the customizable interaction map and student profiles based on settings that users can adjust. We illustrate the use of the software with an educational assessment example. [ABSTRACT FROM AUTHOR]

Massive Open Online Courses (MOOCs) are revolutionizing online education and have become a popular teaching platform. However, traditional MOOCs often overlook learners' individual needs and preferences when designing learning materials and activities, resulting in suboptimal learning experiences. To address this issue, this paper proposes an approach to identify learners' preferences for different learning styles by analyzing their traces in MOOC environments. The Felder–Silverman Learning Style Model is adopted as it is one of the most widely used models in technology-enhanced learning. This research focuses on developing a reliable predictive model that can accurately identify learning styles. Based on insights gained from our model implementation, we propose MOOCLS (MOOC Learning Styles), an intuitive visualization tool. MOOCLS can help teachers and instructional designers to gain significant insight into the diversity of learning styles within their MOOCs. This will allow them to design activities and content that better support the learning styles of their learners, which can lead to higher learning engagement, improved performance, and reduction in time to learn. [ABSTRACT FROM AUTHOR]

Personalized learning is the shaping of instruction to meet students’ needs to support student learning and improve learning outcomes. While it has received increasing attention in education, limited resources are available to help educators properly leverage assessment data to foster personalized learning. Motivated by this need, we introduce a new visualization tool, the interaction map, to foster personalized learning based on assessment data. The interaction map approach is engineered by the latent space item response model, a recent development in assessment data-leveraging social network analysis methodologies. In the interaction map, students and test items are mapped into a two-dimensional geometric space, in which their distances tell us about the student’s strengths and weaknesses with individual or groups of test items given their overall ability levels. Student profiles can be generated based on these distances to display individual student strengths and weaknesses. Finally, we introduce a user-friendly, free web-based software IntMap in which users can upload their own assessment data and view the customizable interaction map and student profiles based on settings that users can adjust. We illustrate the use of the software with an educational assessment example.

Copyright of Journal of Shanghai Jiaotong University (Science) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Code annotations are used mainly in modern Java software, and their primary purpose is to configure metadata into programmable elements such as methods and classes. The Annotation Sniffer is a stable tool that analyses Java source code and generates a JSON report with code annotations metrics values. In other words, it measures metadata configuration in the Java source file. The Annotation Visualizer is a tool built as a web application to render the visualization using this report as input. In this work, we developed a tool that integrates the Annotation Visualizer as a plugin for the IntelliJ IDEA, a popular Java IDE. This integration allows developers to visualize their current project opened in the IDE without switching to an external environment. With an IDE plugin, developers can potentially benefit from the visualization and the metrics values it can display. Furthermore, IDEs have a marketplace that eases obtaining the tool and increases the probability that the developers might use it.

Recognizing the value of open-source research databases in advancing the art and science of HVAC, in 2014 the ASHRAE Global Thermal Comfort Database II project was launched under the leadership of University of California at Berkeley’s Center for the Built Environment and The University of Sydney’s Indoor Environmental Quality (IEQ) Laboratory. The exercise began with a systematic collection and harmonization of raw data from the last two decades of thermal comfort field studies around the world. The ASHRAE Global Thermal Comfort Database II (Comfort Database), now an online, open-source database, includes approximately 81,846 complete sets of objective indoor climatic observations with accompanying “right-here-right-now” subjective evaluations by the building occupants who were exposed to them. The database is intended to support diverse inquiries about thermal comfort in field settings. A simple web-based interface to the database enables filtering on multiple criteria, including building typology, occupancy type, subjects’ demographic variables, subjective thermal comfort states, indoor thermal environmental criteria, calculated comfort indices, environmental control criteria and outdoor meteorological information. Furthermore, a web-based interactive thermal comfort visualization tool has been developed that allows end-users to quickly and interactively explore the data.

Research background: Inflation has always been the core issue of economic research and there are many academic research achievements in this field. In recent years, global inflation has intensified, and many scholars focus on research in this field again, providing certain reference value for countries around the world to formulate corresponding macro policies. Purpose of the article: The five-year impact factors are used as the evaluation criteria in this paper, and 1,637 high-quality documents on inflation from 1906 to 2022 are collected from the Web of Science Core Collection database. Using bibliometrics, a comprehensive review of influ- ential literature in the field of inflation is conducted to reveal the evolution and trends of the field. Methods: First, we focus on these high-quality documents about the descriptive statistical charac- teristics, high cited documents and high impact factor journals. Then, based on the visualization tool, the cooperative network of countries/regions, authors and institutions is depicted and the cooperative relationship between them is determined. At the same time, the most influential countries/regions, authors and institutions are identified by analyzing the citation structure. In addition, through thematic and keyword analysis, the topic hotspots and future research trends of high-quality literature in the field of inflation are deduced. Findings & value added: On the whole, the research on inflation in the United States is relative- ly mature, and has produced a large number of influential academic cooperation results. Finally, we have a series of discussions on the history of inflation in the United States and policy sugges- tions. In the future, governments of various countries, especially the United States, will still face certain challenges in how to formulate policies and measures to mitigate the impact of inflation. [ABSTRACT FROM AUTHOR]

Background: Heart failure (HF) is a significant global clinical and public health challenge, impacting 64.3 million individuals worldwide. To address the scarcity of donor organs, left ventricular assist device (LVAD) implantation has become a crucial intervention for managing end-stage HF, serving as a bridge to heart transplantation or as a destination therapy. Web-based health forums, such as MyLVAD.com, play a vital role as trusted sources of information for individuals with HF symptoms and their caregivers., Objective: We aim to uncover the latent topics within the posts shared by users on the MyLVAD.com website., Methods: Using the latent Dirichlet allocation algorithm and a visualization tool, our objective was to uncover latent topics within the posts shared on the MyLVAD.com website. Through the application of topic modeling techniques, we analyzed 459 posts authored by recipients of LVAD and their family members from 2015 to 2023., Results: This study unveiled 5 prominent themes of concern among patients with LVAD and their family members. These themes included family support (39.5% weight value), encompassing subthemes such as family caregiving roles and emotional or practical support; clothing (23.9% weight value), with subthemes related to comfort, normalcy, and functionality; infection (18.2% weight value), covering driveline infections, prevention, and care; power (12% weight value), involving challenges associated with power dependency; and self-care maintenance, monitoring, and management (6.3% weight value), which included subthemes such as blood tests, monitoring, alarms, and device management., Conclusions: These findings contribute to a better understanding of the experiences and needs of patients implanted with LVAD, providing valuable insights for health care professionals to offer tailored support and care. By using latent Dirichlet allocation to analyze posts from the MyLVAD.com forum, this study sheds light on key topics discussed by users, facilitating improved patient care and enhanced patient-provider communication., (©Semyon Melnikov, Stav Klein, Moni Shahar, David Guy. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.08.2024.)

Copyright of Journal of Computer Science & Technology (JCS&T) is the property of Journal of Computer Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The spread of the newly emerged severe acute respiratory syndrome (SARS-CoV-2) virus has led to more than 430 million confirmed cases, including more than 5.9 million deaths, reported worldwide as of 24 February 2022. Conservation of viral genomes is important for pathogen identification and diagnosis, therapeutics development and epidemiological surveillance to detect the emergence of new viral variants. An intense surveillance of virus variants has led to the identification of Variants of Interest and Variants of Concern. Although these classifications dynamically change as the pandemic evolves, they have been useful to guide public health efforts on containment and mitigation. In this work, we present CovDif, a tool to detect conserved regions between groups of viral genomes. CovDif creates a conservation landscape for each group of genomes of interest and a differential landscape able to highlight differences in the conservation level between groups. CovDif is able to identify loss in conservation due to point mutations, deletions, inversions and chromosomal rearrangements. In this work, we applied CovDif to SARS-CoV-2 clades (G, GH, GR, GV, L, O, S and G) and variants. We identified all regions for any defining SNPs. We also applied CovDif to a group of population genomes and evaluated the conservation of primer regions for current SARS-CoV-2 detection and diagnostic protocols. We found that some of these protocols should be applied with caution as few of the primer-template regions are no longer conserved in some SARS-CoV-2 variants. We conclude that CovDif is a tool that could be widely applied to study the conservation of any group of viral genomes as long as whole genomes exist. [ABSTRACT FROM AUTHOR]

Data visualization aims to explore and analyze data quickly, interactively, and intuitively using visual representations. Faced with the constant growth of data in terms of volume and diversity, visualization techniques must confront the challenge of dealing with increasingly large datasets in terms of representation, interaction, and performance. Therefore, these techniques must be able to effectively convey the characteristics of the information space and inspire discovery. In this article, we present VISUEL, a web dynamic dashboard for data visualization. VISUEL supports multiple coordinated views, integrating visualization techniques such as scatter plots, parallel coordinates, and box plots, and interactive schematic maps to represent information enriched with spatial references. VISUEL is fully interactive, supporting traditional interactions like filtering, selection, brushing and linking, and zooming, among others. It also allows the user to configure the visual representation of their data, by selecting the color and shape of the representations. We illustrate the usefulness of this tool using real-life data related to the wine industry in Argentina. Important aspects of our case study are discovered through the construction and analysis of multiple views.

Background: Over the last decade, there has been growing interest in inverted classroom teaching (ICT) and its various forms within the education sector. Physiology is a core course that bridges basic and clinical medicine, and ICT in physiology has been sporadically practiced to different extents globally. However, students' and teachers' responses and feedback to ICT in physiology are diverse, and the effectiveness of a modified ICT model integrated into regular teaching practice in physiology courses is difficult to assess objectively and quantitatively., Objective: This study aimed to explore the current status and development direction of ICT in physiology in basic medical education using bibliometric visual analysis of the related literature., Methods: A bibliometric analysis of the ICT-related literature in physiology published between 2000 and 2023 was performed using CiteSpace, a bibliometric visualization tool, based on the Web of Science database. Moreover, an in-depth review was performed to summarize the application of ICT in physiology courses worldwide, along with identification of research hot spots and development trends., Results: A total of 42 studies were included for this bibliometric analysis, with the year 2013 marking the commencement of the field. University staff and doctors working at affiliated hospitals represent the core authors of this field, with several research teams forming cooperative relationships and developing research networks. The development of ICT in physiology could be divided into several stages: the introduction stage (2013-2014), extensive practice stage (2015-2019), and modification and growth stage (2020-2023). Gopalan C is the author with the highest citation count of 5 cited publications and has published 14 relevant papers since 2016, with a significant surge from 2019 to 2022. Author collaboration is generally limited in this field, and most academic work has been conducted in independent teams, with minimal cross-team communication. Authors from the United States published the highest number of papers related to ICT in physiology (18 in total, accounting for over 43% of the total papers), and their intermediary centrality was 0.24, indicating strong connections both within the country and internationally. Chinese authors ranked second, publishing 8 papers in the field, although their intermediary centrality was only 0.02, suggesting limited international influence and lower overall research quality. The topics of ICT in physiology research have been multifaceted, covering active learning, autonomous learning, student performance, teaching effect, blended teaching, and others., Conclusions: This bibliometric analysis and literature review provides a comprehensive overview of the history, development process, and future direction of the field of ICT in physiology. These findings can help to strengthen academic exchange and cooperation internationally, while promoting the diversification and effectiveness of ICT in physiology through building academic communities to jointly train emerging medical talents., (© Zonglin He, Botao Zhou, Haixiao Feng, Jian Bai, Yuechun Wang. Originally published in JMIR Medical Education (https://mededu.jmir.org).)

[Display omitted] Colloidal settlement in natural aqueous suspensions is effectively compensated by diffusive movement if particles resist aggregation – a state known as colloidal stability. However, if the settling velocity increases upon aggregation, complex structural features emerge from the directional movement induced by gravity. We present a comprehensive modeling study on the evolution of an aggregated three-dimensional structure due to diffusion, surface interactions, and gravity. The systematic investigation of particle geometry and size revealed three mechanisms: (I) aggregation due to spatial confinement of settled particles, (II) aggregation due to differential settling, whereby fast and slow particles collide, (III) inhibition of aggregation due to fractionation of particles with different settling velocity. A 3D visualization tool allowed us to follow the subtle interplay of these mechanisms and the highly dynamic hierarchical self-assembly of aggregates. It revealed how the balance of the different interactions determines the actual rate of aggregation. [ABSTRACT FROM AUTHOR]

Humans still play a key role in air traffic control but their performances limit the capacity of the airspace and are responsible for delays. At the tactical level, even though air traffic controllers (ATCO) are trained for years, their performances are limited. In this article, we first isolated the tactical horizontal deconfliction task and explained its mathematical complexity. We observed through a simple experiment conducted on trainee and experienced ATCOs its complexity on random traffic in a part-task trainer displaying two to five aircraft trajectories at the same altitude. We compared performances of trainee ATCOs with experienced ATCOs using two different displays: a basic display showing information on aircraft positions and a dynamic visualization tool that represents the conflicting portions of aircraft trajectories and the evolution of the conflict zone when the user adds a maneuver to an aircraft. The tool allows the user to dynamically check the potential conflicting zones with the computer mouse before making a maneuver decision. Results showed that in easy situations (two aircraft), performance was similar with both displays and groups. However, as the complexity of the situations grows (from three to five aircraft), the dynamic visualization tool enables users to solve the conflicts more efficiently. Using the tool leads to fewer unsolved conflicts. Even if experienced ATCOs performed much better than trainee ATCOs on complex situations, they also performed much better with the conflict visualization tool than without on such situations. [ABSTRACT FROM AUTHOR]

Shape memory polymer (SMP) foam is often proposed as the future alternative of coils in aneurysm treatment devices. Present work numerically investigates the unsteady, three-dimensional simulation of blood flow in a cerebral aneurysm filled with SMP foam. Simulations are conducted on patient-specific geometries with realistic blood velocity waveform imposed at the inlet while SMP foam is treated as a porous medium. The present study introduces a "loading risk map" that helps to visualize the hemodynamic effect of foam insertion on the aneurysm sac and neck. The loading risk maps suggest that while the SMP foam subdues the flow and wall shear pulsations in the aneurysm sac, the pressure distribution is minimally affected. The maps suggest that while the downstream lip is the most risk-prone site for both geometries, downstream vascular anatomy significantly influences foam efficiency in reducing pressure and wall shear stress loading. [ABSTRACT FROM AUTHOR]

Copyright of Thermology International is the property of European Association of Thermology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background Large granular lymphocyte (LGL) leukemia is an uncommon cancer characterized by sustained clonal proliferation of LGL cells. Antibodies reactive to retroviruses have been documented in the serum of patients with LGL leukemia. Culture or molecular approaches have to date not been successful in identifying a retrovirus. Methods Because a retrovirus must integrate into the genome of an infected cell, we focused our efforts on detecting a novel retrovirus integration site in the clonally expanded LGL cells. We present a new computational tool that uses long-insert mate pair sequence data to search the genome of LGL leukemia cells for retrovirus integration sites. We also utilize recently published methods to interrogate the status of polymorphic human endogenous retrovirus type K (HERV-K) provirus in patient genomes. Results Our data show that there are no new retrovirus insertions in LGL genomes of LGL leukemia patients. However, our insertion call tool did detect four HERV-K provirus integration sites that are polymorphic in the human population but absent from the human reference genome, hg19. To determine if the prevalence of these or other polymorphic proviral HERV-Ks differed between LGL leukemia patients and the general population, we used a recently developed tool that reports sites in the human genome occupied by a known proviral HERV-K. We report that there are significant differences in the number of polymorphic HERV-Ks in the genomes of LGL leukemia patients of European origin compared to individuals with European ancestry in the 1000 genomes (KGP) data. Conclusions Our study confirms that the clonal expansion of LGL cells in LGL leukemia is not driven by the integration of a new infectious or endogenous retrovirus, although we do not rule out that these cells are responding to retroviral antigens produced in other cell types. However, our computational analyses revealed that the genomes of LGL leukemia patients carry a higher burden of polymorphic HERV-K proviruses compare to individuals from KGP of European ancestry. Our research emphasizes the merits of comprehensive genomic assessment of HERV-K in cancer samples and suggests that further analyses to determine contributions of HERV-K to LGL leukemia are warranted.

Abstract Background One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing FASTQ sequencing data, visualizing which organisms are present in the data can be useful, especially with metagenomics data or data suspected to be contaminated. Here, we describe the development and application of a command-line tool, Keanu, for visualizing and exploring sample content in metagenomics data. We developed Keanu as an interactive tool to make viewing complex data easier. Results Keanu, a tool for exploring sequence content, helps a user to understand the presence and abundance of organisms in a sample by analyzing alignments against a database that contains taxonomy data and displaying them in an interactive web page. The content of a sample can be presented either as a collapsible tree, with node size indicating abundance, or as a bilevel partition graph, with arc size indicating abundance. Here, we illustrate how Keanu works by exploring shotgun metagenomics data from a sample collected from a bluff that contained paleosols and a krotovina in an alpine site in Ft. Greely, Alaska. Conclusions Keanu provides a simple means by which researchers can explore and visualize species present in sequence data generated from complex communities and environments. Keanu is written in Python and is freely available at https://github.com/IGBB/keanu.

In recent years, the need for robotic fleets in large warehouse environments has constantly increased. The customers require faster services concerning the delivery of their products, making the use of systems such as robots and order-management software more than essential. Numerous researchers have studied the problem of robot routing in a warehouse environment, aiming to suggest an efficient model concerning the robotic fleet’s management. In this research work, a methodology is proposed, providing feasible solutions for optimal pathfinding. A novel algorithm is proposed, which combines Dijkstra’s and Kuhn–Munkers algorithms efficiently. The proposed system considers the factor of energy consumption and chooses the optimal route. Moreover, the algorithm decides when a robot must head to a charging station. Finally, a software tool to visualize the movements of the robotic fleet and the real-time updates of the warehouse environment was developed.

The spread of the newly emerged severe acute respiratory syndrome (SARS-CoV-2) virus has led to more than 430 million confirmed cases, including more than 5.9 million deaths, reported worldwide as of 24 February 2022. Conservation of viral genomes is important for pathogen identification and diagnosis, therapeutics development and epidemiological surveillance to detect the emergence of new viral variants. An intense surveillance of virus variants has led to the identification of Variants of Interest and Variants of Concern. Although these classifications dynamically change as the pandemic evolves, they have been useful to guide public health efforts on containment and mitigation. In this work, we present CovDif, a tool to detect conserved regions between groups of viral genomes. CovDif creates a conservation landscape for each group of genomes of interest and a differential landscape able to highlight differences in the conservation level between groups. CovDif is able to identify loss in conservation due to point mutations, deletions, inversions and chromosomal rearrangements. In this work, we applied CovDif to SARS-CoV-2 clades (G, GH, GR, GV, L, O, S and G) and variants. We identified all regions for any defining SNPs. We also applied CovDif to a group of population genomes and evaluated the conservation of primer regions for current SARS-CoV-2 detection and diagnostic protocols. We found that some of these protocols should be applied with caution as few of the primer-template regions are no longer conserved in some SARS-CoV-2 variants. We conclude that CovDif is a tool that could be widely applied to study the conservation of any group of viral genomes as long as whole genomes exist.

Summary: Underground flow path (UFP) is one of the most significant stratigraphic structures in revealing the distribution of oil or gas from seismic data. We design a domain‐specific visualization system to extract the stratigraphic structures by seed point tracing and explore the seismic data by graph interactions. The seeds are automatically generated by kernel function–based density gradients computation. Users are allowed to adjust the recommended seeds by fine‐tuning them with visual interactions. The seeds are further merged by a weighted quick‐union algorithm to get the link information to construct a graph. Different types of nodes in the graph are designed to enable users to explore the extracted UFP structures intuitively. Finally, we evaluated the proposed approach by performance tests, sensitivity tests, and ground truth tests. The feedback from the domain experts demonstrates that the proposed visualization tool improved the capability of revealing the distribution and geostructures of UFPs compared with the existing methods. [ABSTRACT FROM AUTHOR]

Climate informatics connects climate science and data analytics to further the knowledge and understanding of climate data and its applications. The utilization of climate models has been at the core of climate informatics research. However, the correspondence between modelling predictions of climate parameters and their observed values remains an under-investigated issue. In this study, an analytical framework is presented that compares model-predicted values of climate parameters with their observed historic records. The resulting framework is a standardized methodology for operating climate data that can aid researchers and practitioners in performing comparison analysis. A visualization software tool named Weather Analysis Regional Model (WARM) is designed to implement the analytical framework. WARM operates in two regimes: one that compares climate data hosted on the web application and the second one that allows users to input their own datasets. Comparison results supplied by WARM can inform decision-making that employs climate model predictions. • Suggested analytics framework comparing predicted and observed climate parameters. • Visualization tool Weather Analysis Regional Model (WARM) implements the framework. • Case studies demonstrate the framework workflow as well as functional features. • Framework and WARM provide trust and transparency to researchers and practitioners. • Results show that regional models capture future climate but not granular trends. [ABSTRACT FROM AUTHOR]